This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Antimicrobial peptides are small peptides encoded by genes. The research area of antimicrobial peptides has attracted intense attention in recent years because their potential use in the cure of infectious diseases caused by pathogens that have become counteractive to traditional antibiotics. There exist huge amounts of antimicrobial peptides research articles and this number is continuously increasing. Although some biomedical databases, such as PubMed, have been well established, they provide only query-based information retrieval and end-users need to manually find out relevant information from thousands of retrieved articles. In this project, we investigate various document clustering as well as other text mining methods for antimicrobial peptides literature.